Information is increasingly being represented as digital bits of data and stored within electronic databases. These databases often include extremely large numbers of records containing data fields reflecting an endless variety of objects. Some databases, for example, contain the full text of judicial opinions issued by every court in the United States for the past one hundred and fifty years. Other databases may be filled with data fields containing particularized information about vast numbers of individuals (e.g., names, addresses, telephone numbers, etc.). As more information is stored in these databases, the larger these data compilations become.
Among the many advantages associated with electronic storage is the fact that any given database can be searched for the purpose of retrieving individual data records (e.g., documents) that may be of particular interest to the user. One of the ways to perform this search is to simply determine which data records, if any, contain a certain keyword. This determination is accomplished by comparing the keyword with each record in the database and assessing whether the keyword is present or absent. In addition, database users can search for data records that contain a variety of keyword combinations (e.g., "cats" and "dogs", etc.). This operation, known as a Boolean search, uses the conjunctions "AND", "OR", and "NOT" (among others) to join keywords in an effort to more precisely define and/or simplify the database search. For example, if a user joins the keywords "cats" and "dogs" with the conjunction "AND" and inputs the query "cats AND dogs", only those records that contain both the term "cats" and the term "dogs" will be retrieved.
The problem with this Boolean search however, is that a computer typically makes use of substantial memory space and computing time to perform logical combinations of sets of documents corresponding to the keyword search results. It is therefore desireable to create a system that performs logical combinations on set elements that is space and computation time efficient.